With AI, edge computing is seeing transitions to the intelligent edge

The power of cloud computing today has expanded from data centers to the edge of networks. This edge is becoming essential as organizations across all industries deal with ever-growing amounts of data, more complex operations, and more dynamic, competitive markets. To meet business needs, hyper-scale cloud providers, IT companies, and connectivity providers are turning to edge computing and edge intelligence. As communication between connected devices generates voluminous amounts of data, these data need to be quickly processed and executed. It is reported that over 20 billion IoT-connected devices have already been installed. And the number is predicted to reach 75.44 billion by 2025.

Edge computing is a technology that is bound to make data processing easy by bringing decentralized computing power as close as possible to the origin of the data. By doing so, the distance between connected devices and the cloud gets close, making things easy for the networking architecture. With advances and the integration of AI, it is now approaching the intelligent edge, which gleans, communicates, generates, and assesses data in near real-time.

According to Deloitte, businesses can enable greater efficiencies and valuable new use cases with the help of the intelligent edge. These include more efficient use of bandwidth and greater network visibility; resiliency against poor, unreliable, and lost connectivity; support for low-latency use cases and fast response times; greater automation and autonomy; and more control over data triage, normalization, residency, and privacy. The intelligent edge can also deliver greater visibility into network conditions and an awareness of the operating environment.

Powering Intelligent Edge Innovation 

As innovations in cloud computing have attracted much attention from the industry, the advancements at the edge are also becoming equally remarkable. The surge deployment of the intelligent cloud and intelligent edge application patterns are now altering the way businesses interact with digital information and coalesce the physical and digital worlds for greater societal benefit and customer innovation.

Enabled by the database management system, the intelligent edge can help lessen reliance on network performance, minimize threats through a holistic security approach, maintain compliance, improve reliability through consistent app development across cloud and edge, augment bottom lines by lowering overhead expenses and provide seamless user experience through simplified device management. It also allows businesses to gain much greater visibility into their physical operations while subbing AI to handle more high-demand tasks autonomously.

While intelligence edge delivers greater capabilities to businesses, realizing its full power will somewhat require collaborations and orchestration across edge hardware manufacturers, hyper-scale cloud services, IT companies, and connectivity providers.

Intelligent Edge – The Future of AI

AI technology is all around us now, and it will soon be everywhere. Its applications in recent years have improved considerably, traversing from smartphones to personal assistants and recommendation systems to video/audio surveillance. The adoption and maturation of AI is a key enabler of edge networks. Increasingly, chips that are specialized and optimized to run AI and machine learning tasks are moving into edge appliances, according to Deloitte. The amalgamation of specialized chips and AI capabilities makes the edge intelligent, with use cases such as computer vision, data analysis, and deep learning shortening and stimulating the decision loop.